In today's corporate world, businesses keep large volumes of various data, such as accounting information, customer information, business specific data. With the growth of these volumes of data, management of databases of the business systems becomes more problematic. In order to minimize access times and costs, some business systems move dormant “read-only” data into dedicated archive systems, which are less expensive than the main database systems. For example, the archived data may be stored on cheaper storing medias, such as tapes and disks. The archiving of data provides businesses with long-term access to various data that may be required to be accessed in the future, for example, in a legal proceeding.
There are existing archiving system solutions on the market. These archiving system solutions perform archiving operations by selecting data objects from a database and writing the data objects into archive files, upon which, the corresponding data objects are deleted from the database, after ensuring that the data was successfully written into the archive files. Data objects written into a single archive file are processed by a single delete job, i.e. a computer process. Thus, a single delete job is required for every newly created archive file in order to delete the archived data objects from the database. Moreover, the deletion operations in these archiving systems do not halt until all the data objects written into a single archive file are deleted from the database. The number of the created delete jobs and the duration of execution of the created delete jobs may affect the overall system performance. For example, a large number of delete jobs may affect the allocation of processing resources, if delete jobs are occupying resources necessary for more important system processes. However, in the archiving systems currently utilized on the market, the system managers are not provided with any options to configure the archive system to control the number of delete jobs created, and thus are not able to control allocation of processing resources and overall system performance.
Alternatively, some existing archiving systems store data to be archived in a marked-up form, for example in an Extensible Markup Language (XML) form, by creating an archived XML object for each data object to be archived. In these systems, there is a delete job created for each XML object, i.e. for each data object to be archived. Thus, the number of the created delete jobs in these systems is even greater than in the systems storing data objects in the archive files, and the above-stated problems are aggravated.
What is needed, therefore, is a solution that overcomes these and other shortcomings of the prior art.